A novel approach to assessing validity in sports performance research: integrating expert practitioner opinion into the statistical analysis

Kyprianou, Efthymios; Lolli, Lorenzo; Haddad, Hani Al; Salvo, Valter Di; Varley, Matthew C.; Villanueva, Alberto Méndez; Gregson, Warren; Weston, Matthew

doi:10.1080/24733938.2019.1617433

Cited by 14 publications

(18 citation statements)

References 30 publications

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“…The most common tests were the Kolmogorov-Smirnov and Shapiro-Wilk normality tests, the measures of asymmetry dispersion and kurtosis, the bidirectional analysis of variance (ANOVA), and the size of the effect to measure the magnitude of the phenomenon, which can be seen in Table 6. The studies by Kyprianou et al 44 and Massard et al 45 sought to escape traditional description by using equivalence testing through the Two one-sided test (TOST) and grouping techniques widely used in machine learning, respectively. This, therefore, demonstrates that data science is not yet standardized in the field of science applied to football.…”

Section: Discussion and Implications For Practice And Researchmentioning

confidence: 99%

A systematic review of load control in football using a Global Navigation Satellite System (GNSS)

Principe

Vale

Nunes

2020

Motriz: rev. educ. fis.

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Section: Discussion and Implications For Practice And Researchmentioning

confidence: 99%

A systematic review of load control in football using a Global Navigation Satellite System (GNSS)

Principe

Vale

Nunes

2020

Motriz: rev. educ. fis.

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“…A recent study however demonstrates its application. Kyprianou et al 64 elicited the experience and opinion of 49 elite soccer practitioners regarding what they would consider to be an acceptable level of measurement error when measuring sprint speed. They then used the median response from their survey respondents to set equivalence bounds for the smallest effect size of interest when comparing the agreement of two measures of maximal sprint speed.…”

Section: What Can We Do?mentioning

confidence: 99%

Does increasing an athletes’ strength improve sports performance? A critical review with suggestions to help answer this, and other, causal questions in sport science

Steele¹,

Fisher²,

Crawford³

2020

Journal of Trainology

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Researchers and practitioners in sports science aim to generate, and apply, knowledge to improve sports performance. One area of interest is the role that muscular strength, and thus approaches to improve this (i.e. resistance training), has upon sports performance. In this review we briefly consider the evidence regarding an answer to the causal question "Does increasing an athletes' strength improve sports performance?". Design & Methods: We first consider the Applied Research Model for the Sport Sciences (ARMSS) to frame the problem and answer this. We then highlight barriers to answering it (and other causal questions) before offering suggestions to address these. Results: Muscular strength typically differentiates elite and non-elite athletes, and is correlated with proxy measures of sports performance. However, there is insufficient evidence to make a definitive statement regarding the causal effect of muscular strength upon sports performance. Conclusions: Considering the ARMSS, evidence is lacking whether improving muscular strength is causally related to sports performance. Present evidence is primarily observational and cross-sectional, experimental evidence is limited and focused upon proxy measures of sports performance, primarily conducted in small samples, and with little consideration regarding meaningfulness of effects. Suggestions to help improve research in this area and better answer this question include: larger sample sizes, determination of smallest effect sizes of interest for outcomes including muscular strength and proxy measures of sports performance (using both anchoring and/or expert opinion), and use of causal inference methods for observational data (actual sports performance, performance indicators, and fitness measures) including graphical causal diagrams and mediation analysis.

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“…Effects are calculated and presented as simple effect sizes (e.g., mean differences), with standardized effect sizes (i.e., mean difference divided by the pooled SD) also presented but not interpreted. The benefits of simple effect sizes over standardized effect sizes are that they are independent of variance, easier to compute, and scaled in the original units of analysis (3), which maximizes the practical context of findings (17,23). Furthermore, as a player's running velocity is likely constrained by either planned aims (e.g., training) or fulfilling tactical roles (e.g., matches), there is no implication of benefit/ positive or harmful/negative here, so a descriptive presentation of faster or slower is congruent with our research aim.…”

Section: Statistical Analysesmentioning

confidence: 99%

To Measure Peak Velocity in Soccer, Let the Players Sprint

Kyprianou

Salvo

Lolli

et al. 2019

Journal of Strength and Conditioning Research

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To measure peak velocity in soccer, let the players sprint. J Strength Cond Res 36(1): 273-276, 2022-Expressing externals loads relative to a player's individual capacities has potential to enhance understanding of dose-response. Peak velocity is an important metric for the individualization process and is usually measured during a sprint test. Recently, however, peak velocity was reported to be faster during soccer matches when compared with a 40-m sprint test. With the aim of developing the practice of individualized training prescription and match evaluation, we examined whether the aforementioned finding replicates in a group of elite youth soccer players across a broader range of soccer activities. To do this, we compared the peak velocities of 12 full-time male youth soccer players (age 16.3 6 0.8 years) recorded during a 40-m sprint test with peak velocity recorded during their routine activities (matches, sprints, and skillbased conditioning drills: small-sided games [SSG], medium-sided games [MSG], large-sided games [LSG]). All activities were monitored with 10-Hz global positioning systems (Catapult Optimeye S5, version 7.32) with the highest speed attained during each activity retained as the instantaneous peak velocity. Interpretation of clear between-activity differences in peak velocity was based on nonoverlap of the 95% confidence intervals for the mean difference between activities with sprint testing. Peak velocity was clearly faster for the sprint test (8.76 6 0.39 m•s 21 ) when compared with matches (7.94 6 0.49 m•s 21 ), LSG (6.94 6 0.65 m•s 21 ), MSG (6.40 6 0.75 m•s 21 ), and SSG (5.25 6 0.92 m•s 21 ), but not sprints (8.50 6 0.36 m•s 21 ). Our data show the necessity for 40-m sprint testing to determine peak velocity.

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A novel approach to assessing validity in sports performance research: integrating expert practitioner opinion into the statistical analysis

Abstract: The version presented here may differ from the published version or from the version of the record. Please see the repository URL above for details on accessing the published version and note that access may require a subscription.

Cited by 14 publications

References 30 publications

A systematic review of load control in football using a Global Navigation Satellite System (GNSS)

A systematic review of load control in football using a Global Navigation Satellite System (GNSS)

Does increasing an athletes’ strength improve sports performance? A critical review with suggestions to help answer this, and other, causal questions in sport science

To Measure Peak Velocity in Soccer, Let the Players Sprint

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